Metadata-Version: 2.4
Name: DAESIM_preprocess
Version: 0.0.1
Summary: Harvesting environmental forcing data for running the Dynamic Agro-Ecosystem Simulator (DAESIM)
Author-email: Christopher Bradley <christopher.bradley@anu.edu.au>
License-Expression: MIT
Project-URL: Homepage, https://github.com/ChristopherBradley/DAESIM_preprocess
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: rioxarray
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: requests
Requires-Dist: pysheds
Requires-Dist: owslib
Requires-Dist: pyproj
Requires-Dist: matplotlib
Provides-Extra: dev
Requires-Dist: jupyter; extra == "dev"
Requires-Dist: jupytext; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: twine; extra == "dev"
Requires-Dist: build; extra == "dev"
Dynamic: license-file

# DAESIM_preprocess
Harvesting environmental forcing data for running the Dynamic Agro-Ecosystem Simulator (DAESIM)


# Setup locally
1. Download and install Miniconda from https://www.anaconda.com/download/success
2. Add the miniconda filepath to your ~/.zhrc, e.g. export PATH="/opt/miniconda3/bin:$PATH" 
3. brew install gdal
4. git clone https://github.com/ChristopherBradley/DAESIM_preprocess.git
5. cd DAESIM_preprocess
6. conda env create -f environment.yml
7. conda activate DAESIM_preprocess
8. pytest

# Uploading to pip
1. 
